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Visualizing Linear Models

BuchGebunden
167 Seiten
Englisch
Springererschienen am25.02.20211st ed. 2021
Designed to develop fluency with the underlying mathematics and to build a deep understanding of the principles, it's an excellent basis for a one-semester course on statistical theory and linear modeling for intermediate undergraduates or graduate students.Three chapters gradually develop the essentials of linear model theory.mehr
Verfügbare Formate
BuchGebunden
EUR96,29
BuchKartoniert, Paperback
EUR69,54
E-BookPDF1 - PDF WatermarkE-Book
EUR69,54

Produkt

KlappentextDesigned to develop fluency with the underlying mathematics and to build a deep understanding of the principles, it's an excellent basis for a one-semester course on statistical theory and linear modeling for intermediate undergraduates or graduate students.Three chapters gradually develop the essentials of linear model theory.
Zusammenfassung
Features ready-made exercises using a flash card app, available for print or digital use, to improve retention of material

Offers a targeted review of relevant, key background topics

Presents the fundamentals of visualizing linear models in a compact volume, ideal for a one-semester course

Includes supplementary material: sn.pub/extras
Details
ISBN/GTIN978-3-030-64166-5
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2021
Erscheinungsdatum25.02.2021
Auflage1st ed. 2021
Seiten167 Seiten
SpracheEnglisch
IllustrationenXVI, 167 p. 43 illus., 23 illus. in color.
Artikel-Nr.49065066

Inhalt/Kritik

Inhaltsverzeichnis
Preface.- Review: Linear Algebra.- Least-Squares Regression.- Review: Random Vectors.- The Linear Model.- Review: Normality.- Normal Errors.mehr
Kritik
"The author emphasizes didactic aspects in the presentation of the material, especially by utilizing colors and graphs at many places." (Thorsten Dickhaus, zbMATH 1468.62001, 2021)mehr

Autor

Dr. W. D. Brinda is a researcher and lecturer for the department of statistics and data science at Yale University. His research interests include simulated annealing, third moment tensor methods, adaptive estimation, and developing visual ways of understanding statistical concepts. His coauthored work has been published in Statistics and Probability Letters (2019) and IEEE Transactions on Information Theory (2019), among others.
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Brinda, W. D.